Multi-modal imaging of the mechanisms underlying impaired executive attention after traumatic brain injury

创伤性脑损伤（TBI）是导致死亡和长期残疾的主要原因， 仅在美国就有100万人患有慢性执行注意力和认知功能障碍。有一个基金- 对执行注意力的功能和结构机制的知识存在心理上的差距， TBI后的症状没有这些知识，就不可能建立可靠的方法来预测潜在的 康复或最终创造个性化治疗。这项综合研究工作的长期目标是 确定TBI患者认知缺陷的潜在机制，因为这将使准确的分类， 他们的缺陷，更准确的诊断和干预措施的有效性的准确评估。 本提案的总体目标是将执行注意力的临床适用EEG指标与 前前脑中回路（内侧额叶）内结构连接性改变的定量指标 皮质、纹状体和中央丘脑），并评估它们在预测TBI后认知结果中的作用。的 中心假设是，单独测量的电生理反应和解剖损伤， TBI受试者的前前脑中回路将与执行注意力缺陷相关，如通过 ANT，并准确预测广泛的认知结果。这一假设是基于两个人的初步工作。 脑外伤患者的脑电图和弥散MRI研究，以及相关的已发表研究，支持以下基本观点： 在更严重的脑损伤受试者中进行建模。拟议研究的基本原理是， 表征前前脑中间回路和执行注意缺陷之间的关系， 通过生理和解剖测量，将允许深入了解生物学的非生物学水平， 的缺陷和帮助框架机制的方法，以未来的诊断和治疗。指导 根据初步数据，将以两个具体目标对这一假设进行检验。第一个目标是确定 在多大程度上执行注意力损伤，与ANT测量，涉及到伤害相关的变化， 前脑中回路a）生理学（EEG）和B）白色物质连接（扩散MRI）。（c）部分 将整合两种模态，并将其与临床适用的EEG联系起来。{Aim（2）a） 横截面相关和B）通过尖端机器学习纵向预测认知结果 应用于目标1中收集的成像指标的技术。在申请人看来，这种做法是创新的-- 离子，因为他们建议联系注意力障碍，如测量的ANT，以衡量生理 和连接性，并预测认知结果{使用机器学习。亲- 提出的研究是重要的，因为知识的生物学基础的注意力障碍将允许 它作为一种预后措施进行评估，并为有效的个性化干预提供目标。最后， 这些知识有可能使治疗方法的发展，可以显着提高质量 数百万人在TBI后仍然无法恢复其社区内先前的功能水平。

Traumatic Brain Injury (TBI) is a leading cause of death and long-term disability, and there are more than 5.3 million persons in the US alone with chronic executive attention and cognitive dysfunction. There is a funda- mental gap in knowledge of the functional and structural mechanisms underlying executive attention impair- ments after TBI. Without this knowledge it will not be possible to establish reliable ways to predict potential for recovery or, ultimately, create individualized therapies. The long-term goal of this integrated research effort is to identify the mechanism(s) underlying cognitive deficits in TBI patients, as this will enable accurate classifica- tion of their impairments, more accurate prognoses and precise evaluation of the effectiveness of interventions. The overall objective of this proposal is to relate clinically applicable EEG metrics of executive attention to quantitative metrics of structural connectivity alterations within the anterior forebrain mesocircuit (medial frontal cortex, striatum and central thalamus) and to evaluate their role in predicting cognitive outcomes after TBI. The central hypothesis is that individually measured electrophysiologic responses and anatomical injuries within the anterior forebrain mesocircuit of TBI subjects will correlate with executive attention deficits, as measured by the ANT, and accurately predict broad cognitive outcomes. This hypothesis is based on preliminary work from two studies of EEG and diffusion MRI in TBI patients, as well as related published research supporting the underly- ing model in more severely brain-injured subjects. The rationale underlying the proposed research is that char- acterizing the relationship between the anterior forebrain mesocircuit and executive attention deficits at an indi- vidual level, using both physiological and anatomical measurements, will allow insight into the biological un- derpinnings of the deficits and help frame mechanistic approaches to future diagnosis and therapy. Guided by strong preliminary data, this hypothesis will be tested with two specific aims. The first Aim is to determine the extent to which executive attentional impairment, measured with the ANT, relates to injury-related changes in the anterior forebrain mesocircuit a) physiology (EEG) and b) white matter connectivity (diffusion MRI). Part c) of Aim 1 will integrate the two modalities and relate them back to clinically-applicable EEG. {Aim 2 is to a) cross-sectionally relate and b) longitudinally predict cognitive outcomes via cutting-edge machine learning techniques applied to imaging metrics collected in Aim 1.} The approach is innovative, in the applicant's opin- ion, because they propose to link attentional impairments, as measured by the ANT, to measures of physiology and connectivity on an individual basis and predict cognitive outcomes {using machine learning.} The pro- posed research is significant, because knowledge of the biology underlying attention impairment will allow for its evaluation as a prognostic measure and provide targets for effective individualized interventions. Ultimately, such knowledge has the potential to enable development of therapies that can dramatically improve the quality of life for millions that remain unable to return to prior levels of functioning within their communities after TBI.